Method of using follistatin in type 2 diabetes risk prediction

Abstract

A method of using follistatin as a biomarker for early diagnosis and/or prediction of type 2 diabetes, liver follistatin secretion regulated by GCKR, which use is herein reported. Further, a method of composing a biomarker signature for the early prediction of type 2 diabetes in a human is herein disclosed.

1 - 18 . (canceled) 
     
     
         19 . A method for diagnosing or predicting the development of short-term, high-risk, type 2 diabetes in a human subject, the method comprising measuring the level of follistatin and at least one further biomarker in the blood of the human subject, and comparing the measured blood levels with a model value based on averaged blood level values from a group of human subjects identified as having a high risk of developing short-term, high-risk type 2 diabetes. 
     
     
         20 . The method of  claim 19 , wherein the development of short-term, high-risk, type 2 diabetes is predicted to occur in the human subject in less than 10 years. 
     
     
         21 . The method of  claim 19 , further comprising utilizing k-means clustering to assess type 2 diabetes progression risk levels using follistatin and at least one further biomarker selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         22 . The method of  claim 19 , further comprising evaluating available biomarkers by recursive feature elimination for building a risk prediction model to diagnose or predict the development of short-term, high-risk type 2 diabetes in a human subject. 
     
     
         23 . The method of  claim 19 , wherein the at least one further biomarker is selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         24 . The method of  claim 19 , further comprising measuring blood levels of at least two further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         25 . The method of  claim 24 , further comprising measuring blood levels of at least three further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         26 . The method of  claim 24 , further comprising measuring blood levels of at least four further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         27 . A method for composing a biomarker signature for the early prediction of type 2 diabetes in a human subject comprising measuring blood levels from the human subject of follistatin and at least one further biomarker selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c , and comparing the measured blood levels with a model value based on averaged blood level values from a group of humans having a high risk of developing type 2 diabetes in less than 10 years. 
     
     
         28 . The method of  claim 27 , further comprising measuring blood levels of at least two further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         29 . The method of  claim 28 , further comprising measuring blood levels of at least three further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         30 . The method of  claim 28 , further comprising measuring blood levels of at least four further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         31 . A method for diagnosing or predicting the development of short-term, high-risk type 2 diabetes in a human subject comprising obtaining a blood sample from a human subject, measuring blood levels of follistatin, and comparing the measured blood levels with a model value based on averaged blood follistatin level values from a group of human subjects having a high risk of developing type 2 diabetes in less than 10 years. 
     
     
         32 . The method of  claim 31 , further comprising utilizing k-means clustering to assess type 2 diabetes progression risk levels using at least one further biomarker selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         33 . The method of  claim 31 , further comprising evaluating available biomarkers by recursive feature elimination in a risk prediction model to diagnose or predict the development of short-term, high-risk type 2 diabetes in a human subject. 
     
     
         34 . The method of  claim 31 , further comprising composing a biomarker signature for the early prediction of type 2 diabetes in a human, by measuring blood levels from the human subject of follistatin and at least one further biomarker selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c , and comparing the measured blood levels with a model value based on averaged blood level values from a group of human subjects having a high risk of developing type 2 diabetes in less than 10 years. 
     
     
         35 . The method of  claim 34 , wherein the biomarker signature is composed by measuring blood levels of at least two further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         36 . The method of  claim 35 , further comprising measuring blood levels of at least three further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c . 
     
     
         37 . The method of  claim 35 , further comprising measuring blood levels of at least four further biomarkers selected from baseline HbA 1c , proinsulin, C-peptide, or 48-month HbA 1c .